Using Artificial Intelligence to Characterize the Dynamics of Seismic Risk

The Pacific Northwest has the potential to experience large earthquakes (magnitude ~9) along the Cascadia Subduction Zone (CSZ) fault, which is located approximately 120 km off the city of Vancouver. The last CSZ earthquake occurred in 1700, and it is expected to happen every 500 years. An occurrence of this event could lead to large economic and social consequences, which raises an importance of seismic risk assessment in this region. However, seismic risk is subject to change over time due to variations in the built environment (e.g., aging infrastructure) and population shifts. The Covid-19 pandemic is an ongoing issue in British Columbia (and the world) that has changed population distribution dramatically across the region. Under such circumstances, our understanding of seismic risk and its consequences might be substantially different from what is anticipated per the existing risk models In Canada. This research aims to utilize Artificial Intelligence (AI) methods to characterize the dynamics of risk associated with changes in population distribution due to pandemics, which will provide a dynamic setup to continuously evaluate seismic risk. This framework will also serve as an adaptive decision-making tool to evaluate policy measures and their implications on community resilience.

Faculty Supervisor:

Carlos Molina Hutt

Student:

Partner:

Nanyang Technological University

Discipline:

Engineering

Sector:

Education

University:

The University of British Columbia

Program: